Deploy Smarter Connected Devices with AI at the Edge

We have production experience with MQTT (via AWS IoT Core, EMQX, and Mosquitto), AMQP (RabbitMQ), CoAP for constrained devices, BLE for proximity use cases, and LoRaWAN for long-range low-power sensor networks. The protocol choice depends on your device hardware, connectivity environment, message frequency, and latency requirements. We conduct a technical architecture session in the first two weeks to select the protocol stack and broker infrastructure before building the ingestion layer.

Time-series data at IoT scale requires a different storage strategy than transactional databases. We use InfluxDB, TimescaleDB (PostgreSQL extension), or AWS Timestream depending on your query patterns, retention requirements, and existing infrastructure. For ingestion, we front the database with a streaming layer, Kafka or AWS Kinesis, that buffers burst traffic and enables multiple consumers (dashboards, ML pipelines, alerting systems) to process the same event stream independently. For a fleet of 10,000 devices sending telemetry every 30 seconds, that is roughly 1.15 billion events per year; we size and benchmark the pipeline before go-live.

Both. Brownfield integration, connecting an existing device fleet to a new cloud platform, is often where we add the most value. The typical engagement starts with a device protocol audit: we document what messages devices currently send, in what format, at what frequency, and with what reliability guarantees. From there, we design an ingestion adapter that normalizes legacy formats into a canonical schema, build the cloud platform against that schema, and then optionally work with your hardware team to update device firmware to the new schema over time. We do not manufacture hardware or write low-level C firmware, but we interface with teams and vendors who do.

A focused first IoT release with device registration, telemetry ingestion, a real-time dashboard and basic alerting is a Production Application engagement: $60K to $200K over 3 to 5 months with a team of 3 to 4 engineers. Adding fleet management, OTA updates and mobile apps extends scope beyond that range, so we plan it as a second phase. These estimates assume the device hardware and firmware are already functional and sending data; if you need co-development with a hardware partner, add discovery time. We recommend a 4-week paid discovery phase for any IoT project where the device protocol is not yet finalized.

IoT security operates at three layers: device identity, transport security, and cloud authorization. For device identity, we use X.509 certificates issued per device at provisioning time. Each device has a unique private key that never leaves the device. Transport is TLS 1.2 minimum for MQTT and HTTPS connections. On the cloud side, AWS IoT Core policies or equivalent restrict each device to publishing only to its own topic namespace, preventing a compromised device from spoofing others. For edge cases, devices that cannot support TLS due to compute constraints, we implement shared-secret authentication with message signing and replay protection. We also build a device certificate revocation workflow so compromised devices can be isolated without taking down the fleet.